The economic impact of public health measures to contain the Covid-19 novel coronavirus is a matter of contentious debate. Given the high uncertainties, there is a need for combined epidemiological-macroeconomic scenarios.

This paper presents a model for developing such scenarios. The epidemiological sub-model is a discrete-time matrix implementation of a SEIR (susceptible, exposed, infectious and recovered) model. This approach avoids known problems with the more usual set of continuous-time differential equations. The post-Keynesian macroeconomic sub-model is a stylized representation of the US economy with three sectors: core, social (most impacted by social distancing), and hospital, which may experience excessive demand.

Simulations with the model show the clear superiority of a rigorous testing and contact tracing regime in which infected individuals, symptomatic or not, are isolated. Social distancing leads to an abrupt and deep recession. With expanded unemployment benefits, the drop is shallower. When testing and contact tracing is introduced, social spending can be scaled back and the economy recovers quickly. Ending social distancing without a testing and tracing regime leads to a high death toll and severe economic impacts. The results suggest that social distancing and fiscal stimulus have had their desired effects of reducing the health and economic impacts of the disease.